Logistic regression of metastatic tropism based on INCOMMON classes.

Usage

met_tropism(x, gene, tumor_type, metastatic_site)

Arguments

x: An object of class 'INCOMMON' containing the classification results as produced by function classify.
gene: The gene on which patient's stratification is based.
tumor_type: The tumor type of patients to stratify.
metastatic_site: The target organ of metastatic diffusion.

Value

An object of class 'INCOMMON' containing an additional object survival. Logistic regression of metastatic tropism based on INCOMMON classes.

Examples

# First load example classified data
data(MSK_classified)
# Estimate the metastatic propensity associated with mutant TP53 with vs
# without CNA in BRCA, with respect to the Liver.
MSK_classified = met_tropism(x = MSK_classified, tumor_type = 'BRCA', gene = 'TP53', metastatic_site = 'Liver')
#> ℹ There are 20289 different genotypes
#> ℹ The most abundant genotypes are:
#> • Mutant TP53 with LOH (562 Samples, Frequency 0.02)
#> • Mutant KRAS without AMP (199 Samples, Frequency 0.01)
#> • Mutant KRAS without AMP,Mutant TP53 with LOH (149 Samples, Frequency 0.01)
#> Waiting for profiling to be done...
#> Waiting for profiling to be done...
#> # A tibble: 1 × 7
#>   gene  metastatic_site class                   OR   low    up p.value
#>   <chr> <chr>           <chr>                <dbl> <dbl> <dbl>   <dbl>
#> 1 TP53  Liver           Mutant TP53 with LOH  1.36 0.334  9.13   0.699